Job
- Level
- Senior
- Location
- Dusseldorf, Darmstadt
- Working Model
- Hybrid, Onsite
- Job Field
- Data, Application
- Employment Type
- Full Time
- Contract Type
- Permanent employment
Job Summary
In this role, you will develop scalable data models for scientific applications, integrate lab data via APIs, and implement solutions in Python while working closely with customers and scientists.
Job Technologies
Your role in the team
- You will be a key team member in a unique partnership to industrialize Scientific AI. As such, you will engage directly with customers onsite a few days per week in the Frankfurt region, building strong relationships, gaining a deep understanding of their scientific data challenges and requirements, and accelerating solutions.
- Design and implement extensible, reusable data models that efficiently capture and organize scientific data for scientific use cases, ensuring scalability and future adaptability.
- Translate scientific data workflows into robust solutions leveraging the Tetra Data Platform.
- Own, scope, prototype, and implement solutions including: Data model design (tabular & JSON), Python-based parser development, Lab software (e.g., ELN/LIMS) integration via APIs, Data visualization and app development in Python (using app frameworks like Streamlit and plotting tools like holoviews and Plotly).
- Collaborate with Scientific Business Analysts (SBAs), customer scientists, and applied AI engineers to develop and deploy models (ML, AI, mechanistic, statistical, hybrid).
- Programmatically interrogating proprietary instrument output files.
- Dynamically iterate with scientific end users and technical stakeholders to rapidly drive solution development and adoption through regular demos and meetings.
- Proactively communicate implementation progress and deliver demos to customer stakeholders.
- Zusammenarbeit mit dem Produktteam, um unsere Roadmap zu entwickeln und zu priorisieren, indem wir die Schmerzpunkte der Kunden innerhalb und außerhalb der Tetra Data Platform verstehen.
- Rapidly learn new technologies (e.g., new AWS services or scientific analysis applications) to develop and troubleshoot use cases.
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Our expectations of you
Qualifications
- Proven track record of defining, designing, prototyping, and implementing productized AI/ML-driven use cases in cloud environments.
- Collaborated with cross-functional teams, including product managers, software engineers, and scientific stakeholders.
- Performed extensive exploratory data analysis and workflow optimization to enable scientific outcomes not previously possible.
- Engaged diverse audiences, from scientists to executive stakeholders using your excellent communication and storytelling abilities.
- Advised scientists in a consulting capacity to further research, development, and quality testing outcomes.
- Business proficiency of German required (C1 level).
Experience
- PhD with over 4 years or Master's with over 8 years of industry experience in life sciences with extensive domain knowledge in drug discovery (target ID through lead optimization), preclinical development, CMC (all drug modalities), or product quality testing.
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What we offer
- Wettbewerbsfähiges Gehalt und Beteiligung an Eigenkapital in einem schnell wachsenden Unternehmen.
- Supportive, team-oriented culture of continuous improvement.
- Generous paid time off (PTO). Flexible working arrangements - Remote work when not at Customer Sites.
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Topics You Will Work On
Job Locations
About Your Employer
TetraScience
TetraScience develops an innovative cloud platform focused on the harmonization and analysis of scientific data. With a focus on the biopharmaceutical industry, the company enhances the efficiency of research processes through centralized data solutions.
Description
- Company Type
- Established Company
- Working Model
- Hybrid, Onsite
- Industry
- Science, Research
Scientific Data Architect
- Location
- Dusseldorf, Darmstadt
- Working Model
- Hybrid, Onsite
- Diversity
- Open for all genders
